Service Robustness Analysis of Trains by a Simulation Method
Wenzheng Jia, Baohua Mao, Haidong Liu, Shaokuan Chen, Yong Ding
Abstract
Wenzheng Jia, Baohua Mao, Haidong Liu, Shaokuan Chen, Yong Ding
Abstract
This paper discusses the service robustness of trains in scheduled railway timetables, and it also establishes the verification relations between Train Movement Calculation and railway timetables evaluation. A Train Interval Control model with Pure Moving Block Signaling system (P-MBS) is developed and realistic traction characteristics of trains are taken into account. The model can get time intervals between two consecutive trains at block sections and buffer times is used to analysis the robustness, moreover the robustness is calculated according to the extra cost caused by delays. We select a 335.3 kilometers railway dedicated passenger line and four trains to simulate, and the results show that it is an acceptable approach to evaluate the service robustness of trains.
OpenAlex reports 10 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This paper discusses the service robustness of trains in scheduled railway timetables, and it also establishes the verification relations between Train Movement Calculation and railway timetables evaluation. A Train Interval Control model with Pure Moving Block Signaling system (P-MBS) is developed and realistic traction characteristics of trains are taken into account. The model can get time intervals between two consecutive trains at block sections and buffer times is used to analysis the robustness, moreover the robustness is calculated according to the extra cost caused by delays. We select a 335.3 kilometers railway dedicated passenger line and four trains to simulate, and the results show that it is an acceptable approach to evaluate the service robustness of trains.
Key concepts: Train, Robustness (evolution), Computer science, Real-time computing, Simulation, Cartography, Gene, Chemistry